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06/01/2022
The effect of time discretization on the solution of parabolic PDEs with ANNs
We investigate the resolution of parabolic PDEs via Extreme Learning Mac...
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01/18/2022
A sojourn-based approach to semi-Markov Reinforcement Learning
In this paper we introduce a new approach to discrete-time semi-Markov d...
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01/14/2022
Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next
Physics-Informed Neural Networks (PINN) are neural networks (NNs) that e...
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05/24/2021
Heterogeneous Data Fusion Considering Spatial Correlations using Graph Convolutional Networks and its Application in Air Quality Prediction
Heterogeneous data are commonly adopted as the inputs for some models th...
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03/02/2021
Kernel-Based Models for Influence Maximization on Graphs based on Gaussian Process Variance Minimization
The inference of novel knowledge, the discovery of hidden patterns, and ...
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03/23/2020
Julia Language in Machine Learning: Algorithms, Applications, and Open Issues
Machine learning is driving development across many fields in science an...
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08/10/2019
